Personalized  Solutions

For Healthy Lifestyle

For the past couple years, I have been working in the field of early stage diagnosis. For my thesis project I did an in-depth analysis of Photoplethysmogram signal to measure various physiological parameter like blood pressure, HRV parameters etc. Under the guidance of Prof. M. Manivannan, I aimed to develop algorithms for early stage diagnosis of cardiovascular diseases and diabetes using wearables and smart devices.

Introduction Video

Project Developer Internship

Client/ Company

Godrej and Boyce Mfg. Co. Ltd. Mumbai, India


Market Research, Design Principles, Business Model, Wearable Prototype


Dec 2015 - May 2016


Developed MVP for Heart Rate Calculation, Motion Detection & Sending SMS

June - August 2017


Developing MVP for Fall Detection

September - October 2017

Following is a compilation of my work done with Godrej & Boyce  Mfg. Co. Ltd. and Skylar Technologies. The research work mainly includes my M. Tech thesis project at IIT Madras.


Unprecedented advances in urbanization and industrialization comes with the price of impulsively driven lifestyles. This makes contextualizing and measuring health an exacting process. A principal cause of premature deaths is chronic health. A majority of chronic health issues can be categorized under intrinsic diseases. Further classification can involve genetic or acquired traits. The former involves changes in human body because of genetic factors. Acquired newer lifestyles in terms of diet, phycological & physical activities or sleep sums up the latter.

Background Research

Contemporary healthcare systems provide symptom-based solutions. The standing of individual specific factors such as different metabolism and other characteristics is however undermined. These remedies limit their range to symptom-management, deviating from the root cause of the disease. A “Vaidya” of Ayurveda on the other hand, would examine patients through several parameters, even including the influence of environment and the patient’s background. End results include much more personalized suggestions to the patients by categorizing them into distinct body-types. The expert can then suggest therapies and lifestyle checks for nutrition, exercise and sleep based on the individual’s body type.

Market Research

2.5 million wearable were sold in India in 2016


Meeting Stakeholder


Design Principles

Encourage contextual behavior for healthy life

Allow passive monitoring

Help people celebrate their step towards healthy lifestyle

Predict and prevent undesirable body changes

Solution Proposed

Pulse diagnosis is an ancient yet popular technique commonly used for diagnosis. A patient’s health condition can be precisely identified with an in-depth understanding of these pulse waves. It is common knowledge that our heart reflects the physiological condition of the body. Coincidentally, pulse waves work best with capturing the heart rhythm. Any change in the heart rhythm is a consequence of regulatory system influence. This is the way our body responds to immediate needs of organs and systems. A modern technique known as photoplethysmography which uses an optical sensor to measure the blood oxygen level can be closely related to the pulse wave. Pulse technology is the current answer for many fitness bands to measure heart rate. Photoplethysmogram (PPG) signal is topical among researchers however, owing to its use in identifying hypertension, cardiovascular diseases, and diabetes. [1].

Reference: [1] Allen, John. “Photoplethysmography and its application in clinical physiological measurement.” Physiological measurement 28.3 (2007)

Research Work

Minutes of PPG data collected
Number of subject participated
The Difference

Guiding protocols were designed to ensure useful data collection.

Study Of Physiological Parameters Derived From PPG Signal For Personalised Healthcare


Photoplethysmogram indicates health condition of an individual. Important physiological parameters like blood pressure, heart-rate variability, breath rate etc. can be calculated using PPG signal.

For this project many algorithms were designed to calculate time domain, frequency domain and non-linear parameters from PPG. This can be further used to develop models for specific disease identification.

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Skills Acquired

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Machine Learning

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Signal Processing

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Creative Thinking


Northwestern University

The Global Engagement Summit

The GES is a 5 day annual conference, I was one among the 20 international delegates selected for year, 2017. At GES, I got opportunity to discuss my work with some of the most enthusiastic and talented student entrepreneurs from around the world. That’s where I got in touch with start-up Skylar Technologies.

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